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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- poem_sentiment |
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metrics: |
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- accuracy |
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model-index: |
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- name: Bert_uncased_fine_tuned_Reward_Model |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: poem_sentiment |
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type: poem_sentiment |
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config: default |
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split: test |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.875 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Bert_uncased_fine_tuned_Reward_Model |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the poem_sentiment dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0876 |
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- Mse: 0.0876 |
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- Mae: 0.1403 |
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- R2: 0.7389 |
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- Accuracy: 0.875 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 53 | 0.1744 | 0.1744 | 0.2973 | 0.4805 | 0.7885 | |
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| No log | 2.0 | 106 | 0.1074 | 0.1074 | 0.2333 | 0.6801 | 0.8846 | |
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| No log | 3.0 | 159 | 0.1026 | 0.1026 | 0.2134 | 0.6943 | 0.8654 | |
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| No log | 4.0 | 212 | 0.0877 | 0.0877 | 0.1841 | 0.7388 | 0.8942 | |
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| No log | 5.0 | 265 | 0.1000 | 0.1000 | 0.2007 | 0.7021 | 0.8942 | |
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| No log | 6.0 | 318 | 0.0863 | 0.0863 | 0.1738 | 0.7429 | 0.8942 | |
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| No log | 7.0 | 371 | 0.0966 | 0.0966 | 0.1827 | 0.7122 | 0.8846 | |
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| No log | 8.0 | 424 | 0.0946 | 0.0946 | 0.1701 | 0.7183 | 0.8846 | |
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| No log | 9.0 | 477 | 0.0978 | 0.0978 | 0.1658 | 0.7088 | 0.875 | |
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| 0.0516 | 10.0 | 530 | 0.0854 | 0.0854 | 0.1639 | 0.7457 | 0.875 | |
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| 0.0516 | 11.0 | 583 | 0.0947 | 0.0947 | 0.1620 | 0.7181 | 0.8846 | |
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| 0.0516 | 12.0 | 636 | 0.0907 | 0.0907 | 0.1516 | 0.7297 | 0.8846 | |
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| 0.0516 | 13.0 | 689 | 0.0885 | 0.0885 | 0.1546 | 0.7364 | 0.875 | |
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| 0.0516 | 14.0 | 742 | 0.0849 | 0.0849 | 0.1452 | 0.7471 | 0.8942 | |
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| 0.0516 | 15.0 | 795 | 0.0823 | 0.0823 | 0.1428 | 0.7548 | 0.8846 | |
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| 0.0516 | 16.0 | 848 | 0.0864 | 0.0864 | 0.1429 | 0.7427 | 0.8846 | |
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| 0.0516 | 17.0 | 901 | 0.0854 | 0.0854 | 0.1427 | 0.7457 | 0.8846 | |
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| 0.0516 | 18.0 | 954 | 0.0860 | 0.0860 | 0.1429 | 0.7437 | 0.875 | |
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| 0.0059 | 19.0 | 1007 | 0.0871 | 0.0871 | 0.1438 | 0.7406 | 0.875 | |
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| 0.0059 | 20.0 | 1060 | 0.0876 | 0.0876 | 0.1403 | 0.7389 | 0.875 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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